Instructions to use hf-tiny-model-private/tiny-random-YosoForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-YosoForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-YosoForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-YosoForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-YosoForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 984037e43486c727fc496a747edb9889f356be7ac155d9beacf7cea2d0f408fd
- Size of remote file:
- 353 kB
- SHA256:
- b61f168ae027656ec60932a7528bf12c3006d78c7b0efd7f487c0dfdd50a2d47
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